
/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.pig;

import java.io.IOException;
import java.lang.reflect.ParameterizedType;
import java.lang.reflect.Type;
import java.util.List;
import java.util.Stack;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;

import org.apache.pig.classification.InterfaceAudience;
import org.apache.pig.classification.InterfaceStability;
import org.apache.pig.data.Tuple;
import org.apache.pig.impl.PigContext;
import org.apache.pig.impl.logicalLayer.FrontendException;
import org.apache.pig.impl.logicalLayer.schema.Schema;
import org.apache.pig.backend.hadoop.executionengine.physicalLayer.PigLogger;
import org.apache.pig.backend.hadoop.executionengine.physicalLayer.PigProgressable;


/**
 * The class is used to implement functions to be applied to
 * fields in a dataset. The function is applied to each Tuple in the set.
 * The programmer should not make assumptions about state maintained
 * between invocations of the exec() method since the Pig runtime
 * will schedule and localize invocations based on information provided
 * at runtime.  The programmer also should not make assumptions about when or
 * how many times the class will be instantiated, since it may be instantiated
 * multiple times in both the front and back end.
 */
@InterfaceAudience.Public
@InterfaceStability.Stable
public abstract class EvalFunc<T>  {
    /**
     * Reporter to send heartbeats to Hadoop.  If exec will take more than a
     * a few seconds {@link PigProgressable#progress} should be called
     * occasionally to avoid timeouts.  Default Hadoop timeout is 600 seconds.
     */
    protected PigProgressable reporter;

    /**
     * Logging object.  Log calls made on the front end will be sent to
     * pig's log on the client.  Log calls made on the backend will be
     * sent to stdout and can be seen in the Hadoop logs.
     */
    protected Log log = LogFactory.getLog(getClass());

    /**
     * Logger for aggregating warnings.  Any warnings to be sent to the user
     * should be logged to this via {@link PigLogger#warn}.
     */
    protected PigLogger pigLogger;

    private static int nextSchemaId; // for assigning unique ids to UDF columns
    protected String getSchemaName(String name, Schema input) {
        String alias = name + "_";
        if (input!=null && input.getAliases().size() > 0){
            alias += input.getAliases().iterator().next() + "_";
        }

        alias += ++nextSchemaId;
        return alias;
    }
    
    /**
     * Return type of this instance of EvalFunc.
     */
    protected Type returnType;
    
    public EvalFunc(){
        
        //Figure out what the return type is by following the object hierarchy upto the EvalFunc
        
        Class<?> superClass = getClass();
        Type superType = getClass();
        
        Stack<Type> geneticsStack = new Stack<Type>();
        
        // Go up the hierachy of the class up to the EvalFunc
        while (!superClass.isAssignableFrom(EvalFunc.class))
        {
            superType = superClass.getGenericSuperclass();
            superClass = superClass.getSuperclass();
            geneticsStack.push(superType);
        }
        
        // From EvalFunc (superclass), go downward (subclass), 
        // find the first class materialize the genetics
        Type materializedType = null;
        while (!geneticsStack.isEmpty()) {
            Type aType = geneticsStack.pop();
            if (aType instanceof ParameterizedType) {
                // We materialized something, eg, materialized the type to Double,
                // or materialized the type to Map<String, Object>, or materialized the type
                // to T(another genetics). In the 1st case, getActualTypeArguments()
                // returns a class, we can tell easily; In the 2nd and 3th case, 
                // getActualTypeArguments() returns a ParameterizedType, 
                // we cannot tell 2nd case from 3th case.
                // So we need further check if the type inside materializedType 
                // are materialized (case 2)
                materializedType = ((ParameterizedType)aType).getActualTypeArguments()[0];
            }
            Type currentType = materializedType;
            while (currentType instanceof ParameterizedType)
                currentType = ((ParameterizedType)currentType).getActualTypeArguments()[0];
            if (currentType instanceof Class) {
                returnType = materializedType;
                break;
            }
        }

        String errMsg = getClass() + "extends the raw type EvalFunc. It should extend the parameterized type EvalFunc<T> instead.";
        
        if (returnType==null)
            throw new RuntimeException(errMsg);
        
        //Type check the initial, intermediate, and final functions
        if (this instanceof Algebraic){
            Algebraic a = (Algebraic)this;
            
            errMsg = "function of " + getClass().getName() + " is not of the expected type.";
            if (getReturnTypeFromSpec(new FuncSpec(a.getInitial())) != Tuple.class)
                throw new RuntimeException("Initial " + errMsg);
            if (getReturnTypeFromSpec(new FuncSpec(a.getIntermed())) != Tuple.class)
                    throw new RuntimeException("Intermediate " + errMsg);
            if (!getReturnTypeFromSpec(new FuncSpec(a.getFinal())).equals(returnType))
                    throw new RuntimeException("Final " + errMsg);
        }
        
    }
    

    private Type getReturnTypeFromSpec(FuncSpec funcSpec){
        try{
            return ((EvalFunc<?>)PigContext.instantiateFuncFromSpec(funcSpec)).getReturnType();
        }catch (ClassCastException e){
            throw new RuntimeException(funcSpec + " does not specify an eval func", e);
        }
    }
    
    /**
     * Get the Type that this EvalFunc returns.
     * @return Type
     */
    public Type getReturnType(){
        return returnType;
    }
        
    // report that progress is being made (otherwise hadoop times out after 600 seconds working on one outer tuple)
    /**
     * Utility method to allow UDF to report progress.  If exec will take more than a
     * a few seconds {@link PigProgressable#progress} should be called
     * occasionally to avoid timeouts.  Default Hadoop timeout is 600 seconds.
     */
    public final void progress() {
        if (reporter != null) reporter.progress();
        else warn("No reporter object provided to UDF.", PigWarning.PROGRESS_REPORTER_NOT_PROVIDED);
    }
    
    /**
     * Issue a warning.  Warning messages are aggregated and reported to
     * the user.
     * @param msg String message of the warning
     * @param warningEnum type of warning
     */
    public final void warn(String msg, Enum warningEnum) {
    	if(pigLogger != null) pigLogger.warn(this, msg, warningEnum);
    	else log.warn("No logger object provided to UDF: " + this.getClass().getName() + ". " + msg);
    }

    /**
     * Placeholder for cleanup to be performed at the end. User defined functions can override.
     * Default implementation is a no-op.
     */
    public void finish(){}
    
    
    
    /**
     * This callback method must be implemented by all subclasses. This
     * is the method that will be invoked on every Tuple of a given dataset.
     * Since the dataset may be divided up in a variety of ways the programmer
     * should not make assumptions about state that is maintained between
     * invocations of this method.
     * 
     * @param input the Tuple to be processed.
     * @return result, of type T.
     * @throws IOException
     */
    abstract public T exec(Tuple input) throws IOException;
    
    /**
     * Report the schema of the output of this UDF.  Pig will make use of
     * this in error checking, optimization, and planning.  The schema
     * of input data to this UDF is provided.
     * @param input Schema of the input
     * @return Schema of the output
     */
    public Schema outputSchema(Schema input) {
        return null;
    }
    
    /**
     * This function should be overriden to return true for functions that return their values
     * asynchronously.  Currently pig never attempts to execute a function
     * asynchronously.
     * @return true if the function can be executed asynchronously.
     */
    @Deprecated
    public boolean isAsynchronous(){
        return false;
    }


    public PigProgressable getReporter() {
        return reporter;
    }


    /**
     * Set the reporter.  Called by Pig to provide a reference of
     * the reporter to the UDF.
     * @param reporter Hadoop reporter
     */
    public final void setReporter(PigProgressable reporter) {
        this.reporter = reporter;
    }
    
    /**
     * Allow a UDF to specify type specific implementations of itself.  For example,
     * an implementation of arithmetic sum might have int and float implementations,
     * since integer arithmetic performs much better than floating point arithmetic.  Pig's
     * typechecker will call this method and using the returned list plus the schema
     * of the function's input data, decide which implementation of the UDF to use.
     * @return A List containing FuncSpec objects representing the EvalFunc class
     * which can handle the inputs corresponding to the schema in the objects.  Each
     * FuncSpec should be constructed with a schema that describes the input for that
     * implementation.  For example, the sum function above would return two elements in its 
     * list:
     * <ol>
     * <li>FuncSpec(this.getClass().getName(), new Schema(new Schema.FieldSchema(null, DataType.DOUBLE)))
     * <li>FuncSpec(IntSum.getClass().getName(), new Schema(new Schema.FieldSchema(null, DataType.INTEGER)))
     * </ol>
     * This would indicate that the main implementation is used for doubles, and the special
     * implementation IntSum is used for ints.
     */
    public List<FuncSpec> getArgToFuncMapping() throws FrontendException{
        return null;
    }

    /**
     * Allow a UDF to specify a list of files it would like placed in the distributed
     * cache.  These files will be put in the cache for every job the UDF is used in.
     * The default implementation returns null.
     * @return A list of files
     */
    public List<String> getCacheFiles() {
        return null;
    }
    
    public PigLogger getPigLogger() {
        return pigLogger;
    }

    /**
     * Set the PigLogger object.  Called by Pig to provide a reference 
     * to the UDF.
     * @param pigLogger PigLogger object.
     */
    public final void setPigLogger(PigLogger pigLogger) {
        this.pigLogger = pigLogger;
    }
    
    public Log getLogger() {
    	return log;
    }
}
